raster_histogram
Analyze pixel value distributions in raster data bands to understand data patterns and quality for geospatial analysis.
Instructions
Compute histogram of pixel values for each band.
Parameters:
source: path to input raster.
bins: number of histogram bins.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | ||
| bins | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Implementation Reference
- The core handler function for the 'raster_histogram' MCP tool. It reads the input raster, computes histograms for each band using numpy.histogram, and returns the results per band including bin edges.
@gis_mcp.tool() def raster_histogram( source: str, bins: int = 256 ) -> Dict[str, Any]: """ Compute histogram of pixel values for each band. Parameters: - source: path to input raster. - bins: number of histogram bins. """ try: import rasterio import numpy as np import os src_path = os.path.expanduser(source.replace("`", "")) histograms = {} with rasterio.open(src_path) as src: for i in range(1, src.count + 1): band = src.read(i, masked=True) hist, bin_edges = np.histogram(band.compressed(), bins=bins) histograms[f"Band {i}"] = { "histogram": hist.tolist(), "bin_edges": bin_edges.tolist() } return { "status": "success", "histograms": histograms, "message": f"Histogram computed for all bands." } except Exception as e: raise ValueError(f"Failed to compute histogram: {e}") - src/gis_mcp/rasterio_functions.py:11-35 (registration)MCP resource that lists all available rasterio operations, including 'raster_histogram', serving as a tool discovery/registration point.
@gis_mcp.resource("gis://operation/rasterio") def get_rasterio_operations() -> Dict[str, List[str]]: """List available rasterio operations.""" return { "operations": [ "metadata_raster", "get_raster_crs", "clip_raster_with_shapefile", "resample_raster", "reproject_raster", "weighted_band_sum", "concat_bands", "raster_algebra", "compute_ndvi", "raster_histogram", "tile_raster", "raster_band_statistics", "extract_band", "zonal_statistics", "reclassify_raster", "focal_statistics", "hillshade", "write_raster" ] }